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OpenTrain AI is seeking STEM Experts to evaluate, reason, and improve AI training data. You will review complex scientific, mathematical, and technical problems using Python-based calculations and simulations within your domain of expertise.
This remote, contractor role offers about 15 hours per week, onboarding within 24–48 hours, and tasks that can be completed quickly. No formal degree is required if you can demonstrate strong expertise and clear reasoning.
OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI is hiring contractors to help improve advanced AI systems through expert evaluation, scientific reasoning, and technical problem-solving.
AI training is the human side of building artificial intelligence. Experts review model responses, solve challenging problems, and provide accurate examples so AI systems can reason more reliably across technical and scientific subjects.
As a STEM Expert, you will contribute your deep knowledge in at least one scientific or technical discipline. Your work may involve technical problem-solving, scientific reasoning, data analysis, Python-based calculations or simulations, and careful review of AI outputs.
Candidates do not need expertise across every STEM discipline. Relevant expertise may come from academic research, industry, teaching, engineering, independent technical work, or other demonstrated experience. A specific degree or number of years of experience is not strictly required when strong expertise can be demonstrated.
You will solve, review, validate, and explain challenging scientific, mathematical, and technical problems within your area of expertise. Depending on the task, you may interpret equations, datasets, experimental results, technical diagrams, or scientific literature.
You should have strong expertise in at least one relevant STEM or scientific domain and practical proficiency with Python. Experience with tools such as NumPy, SciPy, pandas, SymPy, Jupyter, or other scientific libraries may be useful, but no specific Python library is mandatory.
The work requires careful quantitative reasoning and the ability to identify assumptions, constraints, edge cases, and possible sources of error. Experience validating, reviewing, analyzing, or troubleshooting technical work is important.
Candidates may qualify through strong expertise in one or more of the following areas. Adjacent scientific, engineering, or quantitative disciplines may also be considered when directly relevant.
Compensation is output-based within the advertised $50-$100 per hour range. Payment is based on completed tasks that meet project specifications, and the time required for each task may vary based on complexity, experience, and workflow.
Minimum submission requirements may apply. If selected, you may be expected to begin your first task within 24-48 hours after completing onboarding.
Applicants must be based in one of the listed countries. This project is not open worldwide.